The present invention relates in general to systems or methods relating to the deployment of airbags. In particular, the present invention relates to identifying the upper torso of an occupant so that characteristics relating to the upper torso of the occupant can serve as the basis for making decisions relating to the potential deployment of an airbag.
Conventional collision detection systems typically use accelerometers or weight-based sensors to determine if there has been a vehicle collision to trigger the deployment of an airbag. Such systems are subject to false alarms from severe road conditions, such as a vehicle sliding on ice that then bumps into a curb, and minor impacts, such as the accidental hitting of a parking block while entering a parking lot. It would be desirable for an airbag deployment system to be based on occupant characteristics derived from an image of the occupant because the image of an occupant can be less susceptible to errors caused by rapidly shifting movement or weight.
Airbag deployment systems must perform their functions in a real-time environment. Even a standard video camera can capture as many as 100 images in a single second. Thus, the process from the capturing of a sensor reading or image through the making of a deployment decision must be performed in a prompt and reliable manner. It can be desirable for airbag-related image processing to focus on the upper torso of the occupant. In most airbag deployment situations, the part of the occupant exhibiting the most movement is the upper torso of the occupant. Upper torso movement dominates even in situations where an occupant is not restrained by a seatbelt, with the head moving forward quickly as the upper torso rotates forward along the hip.
Given the constraints of time, airbag deployment systems should be robust to facilitate reliable processing. In order to facilitate resistance to process “noise,” it would be desirable for the process of identifying the upper torso image of the occupant to incorporate iterative processing and a probability-weighted analysis. It can also be desirable for anthropomorphic data as well as information relating the vehicle to be incorporated into certain assumptions made at various points in the process of identifying the upper torso image, or throughout the process of capturing images through generating deployment decisions.